VP, Innovation Lead

LPL Financial LLC; Hyderabad; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

LPL Financial LLC in Hyderabad seeks an Innovation Lead to drive AI/ML strategy, prototype rapid solutions, and lead cloud-native, data-driven engineering efforts. You will mentor teams, promote responsible AI, and advance automation across the delivery lifecycle.

The role emphasizes hands-on development with .NET/Java foundations, scalable architectures, and collaboration with business units to deliver value at speed.

Qualifications

• Hands-on knowledge of AI/ML concepts, RAG, and LLM evaluation.
• Experience with building AI-powered features and intelligent assistants.
• Strong backend and cloud engineering fundamentals.

Responsibilities

• Define and drive AI/innovation roadmap aligned to business goals.
• Prototype AI solutions and convert proofs-of-concept to production.
• Architect AWS-based solutions with scalable data pipelines.
• Lead engineering teams and promote modernDevOps practices.
• Establish governance for Responsible AI, privacy, and cost control.
• Mentor teams in CI/CD, testing, and automated workflows.

Skills

AI & ML concepts

RAG pipelines

LLMs

C#/Java

Python/TypeScript

Prompt engineering

Tools

AWS

Terraform

Docker

Kubernetes

Job description

Where Ambition Meets Innovation At LPL’s Global Capability Center, you'll find a collaborative culture where your voice matters, integrity guides every decision, and technology fuels progress. Your skills, talents, and ideas will redefine what's possible. LPL's success reflects its exceptional employees, who together pursue one noble purpose: empowering financial advisors to deliver personalized advice for all who need it. We’re proud to be expanding and reaching new heights in Hyderabad. Join us as we create something extraordinary together.

Job Description:

Innovation Lead Role Overview Seeking a visionary and hands-on Innovation Lead to drive the design, prototyping, and delivery of next-generation solutions across the organization. This leader will identify emerging technologies—particularly in Artificial Intelligence / Generative AI, cloud (AWS), and data platforms—and translate them into production-grade capabilities built on a strong .NET/Java engineering foundation. The Innovation Lead will champion rapid experimentation, build reusable innovation frameworks, embed intelligent automation across the software delivery lifecycle, and mentor teams to adopt modern engineering practices at scale.

Key Responsibilities AI & Emerging Technology Innovation Define and drive the AI/innovation roadmap aligned to business strategy and measurable outcomes. Identify, evaluate, and prototype emerging technologies (Generative AI, LLMs, ML, agentic workflows, RAG) and convert successful proof-of-concepts into production solutions. Design and implement AI-powered features such as intelligent assistants, document/data extraction, recommendation systems, forecasting, and anomaly detection. Establish frameworks for LLM integration, prompt engineering, RAG pipelines, vector search, fine-tuning, and model evaluation. Implement Responsible AI practices—governance, bias mitigation, data privacy, guardrails, and cost/performance optimization. Run innovation sprints, hackathons, and tech-scouting to build a culture of experimentation.

Cloud Solution Architecture (AWS) Architect scalable, secure, and cost-optimized solutions on AWS. Design and build using core AWS services: Compute: Lambda, ECS/EKS, EC2 AI/ML: Bedrock, SageMaker, Comprehend, Textract, Kendra Data & Storage: S3, RDS, DynamoDB, Redshift, Aurora Integration: API Gateway, Step Functions, EventBridge, SQS/SNS Observability & Security: CloudWatch, IAM, KMS, Secrets Manager Implement Infrastructure as Code (Terraform / AWS CDK / CloudFormation) for repeatable, automated deployments. Build ephemeral and self-service environments to accelerate prototyping and experimentation. Optimize cloud utilization, performance, and cost.

Data & Database Engineering Design and optimize relational and NoSQL databases (SQL Server, PostgreSQL, MySQL, Oracle, DynamoDB, MongoDB). Architect data pipelines, ETL/ELT flows, and data models supporting analytics and AI workloads. Implement vector databases (pgvector, OpenSearch, Pinecone) to support semantic search and RAG. Ensure data quality, governance, lineage, security, and compliance. Enable data-driven decision-making through dashboards, analytics, and reporting.

Application Engineering (.NET / Java) Lead the design and development of enterprise-grade applications and microservices using .NET (C#) and/or Java (Spring Boot). Define architecture standards, coding best practices, API design (REST/GraphQL/gRPC), and design patterns. Build robust, secure, high-performance backend services and integration layers. Modernize legacy applications and migrate workloads to cloud-native architectures.

Automation & Engineering Excellence Embed intelligent automation across the full software delivery lifecycle. Design and build automated frameworks for: CI/CD and deployment automation Testing (UI, API, end-to-end) using Playwright Infrastructure provisioning and teardown Data generation and environment setup Create configurable mock services, simulators, and stubs for third-party dependencies to enable independent development and testing (success/failure scenarios, timeouts, latency, rate limiting, auth failures, edge cases). Integrate automation and quality gates into CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins). Enable parallel execution, self-service capabilities, and reusable platforms for engineering teams.

DevOps & Observability Champion DevOps culture—containerization (Docker/Kubernetes), automation, and continuous delivery. Implement monitoring, logging, tracing, and diagnostics for applications and infrastructure. Drive reliability, scalability, security, and execution speed across platforms.

Leadership & Collaboration Mentor and technically lead cross-functional engineering teams. Partner with product, business, and leadership stakeholders to align innovation with strategic goals. Communicate complex technical concepts to technical and non-technical audiences. Evangelize best practices, reusable assets, and a culture of continuous learning.

Required Skills

AI & Machine Learning Hands-on experience with Generative AI / LLMs (OpenAI, Anthropic, AWS Bedrock, Azure OpenAI). Experience with RAG, prompt engineering, embeddings, vector databases, and model evaluation. Familiarity with ML frameworks and MLOps concepts. Understanding of Responsible AI, governance, and security.

Programming & Application Development Strong hands-on expertise in .NET (C#) and/or Java (Spring Boot). Experience designing microservices, APIs, and distributed systems. Working knowledge of Python and TypeScript/JavaScript is a strong plus.

AWS & Cloud Infrastructure IAM, Lambda, ECS/EKS, API Gateway, S3, DynamoDB, RDS/Aurora, Step Functions, EventBridge, CloudWatch. AI/ML services: Bedrock, SageMaker, Textract, Comprehend. Infrastructure as Code: Terraform (preferred), AWS CDK, CloudFormation.

Databases & Data Strong SQL and NoSQL database design and optimization. Data modeling, ETL/ELT pipelines, and data governance. Vector/semantic search technologies.

Automation & DevOps Playwright for UI, API, and end-to-end automation; cross-browser testing (Chrome, Edge, Firefox). Service virtualization & mocking: WireMock, MockServer, Hoverfly, Mountebank, Pact. Containerization: Docker, Kubernetes. CI/CD: GitHub Actions, Azure DevOps, Jenkins. Test data generation and management

Ideal Candidate Profile

12+ years of experience in software engineering, solution architecture, platform engineering, or innovation/R&D roles. Proven track record of taking AI and emerging-technology ideas from concept to production at scale. Strong AWS automation and Infrastructure-as-Code expertise. Deep hands-on .NET and/or Java development background with strong database engineering skills. Demonstrated experience building automation frameworks, mock services, and self-service platforms. Strong understanding of microservices, APIs, distributed systems, cloud-native design, and CI/CD practices. Excellent leadership, communication, and stakeholder-management skills. A builder's mindset—curious, pragmatic, and biased toward rapid experimentation and delivery.

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